| /external/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/ |
| H A D | ctor_double.pass.cpp | 25 assert(d.mean() == 1);
30 assert(d.mean() == 3.5);
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| H A D | param_ctor.pass.cpp | 27 assert(p.mean() == 1);
33 assert(p.mean() == 10);
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| H A D | ctor_param.pass.cpp | 27 assert(d.mean() == 0.25);
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| H A D | param_assign.pass.cpp | 29 assert(p.mean() == .7);
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| H A D | param_copy.pass.cpp | 28 assert(p.mean() == .125);
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| /external/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/ |
| H A D | ctor_double_double.pass.cpp | 15 // explicit normal_distribution(result_type mean = 0, result_type stddev = 1);
25 assert(d.mean() == 0);
31 assert(d.mean() == 14.5);
37 assert(d.mean() == 14.5);
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| H A D | param_ctor.pass.cpp | 27 assert(p.mean() == 0);
34 assert(p.mean() == 10);
41 assert(p.mean() == 10);
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| H A D | ctor_param.pass.cpp | 27 assert(d.mean() == 0.25);
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| H A D | eval.pass.cpp | 42 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); local
48 double d = (u[i] - mean);
59 double x_mean = d.mean();
63 assert(std::abs((mean - x_mean) / x_mean) < 0.01);
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| H A D | eval_param.pass.cpp | 43 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); local
49 double d = (u[i] - mean);
60 double x_mean = p.mean();
64 assert(std::abs((mean - x_mean) / x_mean) < 0.01);
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| H A D | param_assign.pass.cpp | 29 assert(p.mean() == .75);
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| H A D | param_copy.pass.cpp | 28 assert(p.mean() == 10);
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| /external/chromium_org/third_party/webrtc/common_audio/vad/ |
| H A D | vad_gmm.h | 19 // normal distribution with mean and standard deviation (|mean|, |std|).
23 // - mean : mean input in the statistical model, Q7.
29 // |delta| = (|input| - |mean|) / |std|^2.
33 // 1 / |std| * exp(-(|input| - |mean|)^2 / (2 * |std|^2));
35 int16_t mean,
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| /external/skia/tools/ |
| H A D | Stats.h | 17 mean = sum / n;
21 err += (samples[i] - mean) * (samples[i] - mean);
28 double mean; // Estimate of population mean. member in struct:Stats
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| /external/webrtc/src/common_audio/vad/ |
| H A D | vad_gmm.h | 19 // normal distribution with mean and standard deviation (|mean|, |std|).
23 // - mean : mean input in the statistical model, Q7.
29 // |delta| = (|input| - |mean|) / |std|^2.
33 // 1 / |std| * exp(-(|input| - |mean|)^2 / (2 * |std|^2));
35 int16_t mean,
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| /external/linux-tools-perf/perf-3.12.0/tools/perf/util/ |
| H A D | stat.c | 10 delta = val - stats->mean;
11 stats->mean += delta / stats->n;
12 stats->M2 += delta*(val - stats->mean);
23 return stats->mean;
35 * The std dev of the mean is related to the std dev by:
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| H A D | stat.h | 8 double n, mean, M2; member in struct:stats
20 stats->mean = 0.0;
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| /external/valgrind/main/VEX/test/ |
| H A D | rounderr.c | 43 /* Compute the arithmetic mean of a dataset using the recurrence relation
44 mean_(n) = mean(n-1) + (data[n] - mean(n-1))/(n+1) */
45 long double mean = 0; local
50 mean += (data[i * stride] - mean) / (i + 1);
52 return mean;
58 /* Compute the arithmetic mean of a dataset using the
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| /external/lldb/tools/lldb-perf/lib/ |
| H A D | Metric.cpp | 67 T mean = 0; local
72 T delta = x - mean;
73 mean = mean + delta/n;
74 M2 = M2+delta*(x-mean);
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| /external/chromium_org/media/cast/test/utility/ |
| H A D | test_util.cc | 25 mean = sum / num_values;
32 return base::StringPrintf("%f +/- %f", mean, std_dev);
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| H A D | test_util.h | 22 double mean; member in class:media::cast::test::MeanAndError
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| /external/chromium_org/third_party/smhasher/src/ |
| H A D | SpeedTest.cpp | 15 // of the mean.
19 double mean = 0; local
23 mean += v[i];
26 mean /= double(v.size());
28 return mean;
33 double mean = 0; local
37 mean += v[i];
40 mean /= (b-a+1);
42 return mean;
47 double mean local
68 double mean = 0; local
128 double mean = CalcMean(v,a,b); local
[all...] |
| /external/opencv/cv/src/ |
| H A D | cvadapthresh.cpp | 48 CvMat* mean = 0; local
70 mean = dst;
72 CV_CALL( mean = cvCreateMat( rows, cols, CV_8UC1 ));
74 CV_CALL( cvSmooth( src, mean, method == CV_ADAPTIVE_THRESH_MEAN_C ?
89 const uchar* m = mean->data.ptr + i*mean->step;
98 if( mean != dst )
99 cvReleaseMat( &mean );
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| /external/chromium_org/third_party/skia/tools/ |
| H A D | Stats.h | 26 mean = sum / n;
30 err += (samples[i] - mean) * (samples[i] - mean);
59 double mean; // Estimate of population mean.
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| /external/chromium_org/third_party/WebKit/Tools/Scripts/ |
| H A D | sampstat | 32 usage = "usage: %prog [options] [FILES]\n Compute the mean and 95% confidence interval of a sample set.\n Standard input or files must contain two or more decimal numbers, one per line."
47 def standardDeviation(mean, items):
48 deltaSquares = [(item - mean) ** 2 for item in items]
65 mean = arithmeticMean(items)
66 stdDev = standardDeviation(mean, items)
83 mean = arithmeticMean(results) variable
85 confidencePercent = 100 * confidenceInterval / mean
97 print "%s%.2f %s +/- %.2f %s (%.1f%%)" % (prefix, mean, options.unit, confidenceInterval, options.unit, confidencePercent)
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